Industrial plant processes contain embedded systems to achieve process automation. As processes become complex, control is distributed throughout the system. Distributed control refers to embedded processors distributed throughout a plant system to control sub-processes. The embedded processors run programs to monitor an output of a plant sub-process, or subsystem. The output can be a position, a temperature, a pressure, a voltage, or any other parameter appropriate for the sub-process. Sensors convert the parameters to electrical signals and the electrical signals are quantified for the embedded processors using analog to digital (A/D) converters. Based on the given value of a parameter, an embedded processor changes the sub-process inputs until the sub-process output meets the target value for the parameter.
Proportional integral derivative (PID) controllers are often used to control the individual sub-processes. For a proportional controller, the controller output is proportional to the error in a measurement of the parameter of interest, where error is defined as the difference between the target value of the parameter and the measured value of the parameter. A proportional integral (PI) controller is designed to eliminate an offset associated with a proportional controller by making the controller output proportional to the amount of time the error is present. In a proportional integral derivative (PID) controller, derivative action is added to increase the speed of response and to anticipate changes. The derivative term acts on the rate of change of the error.
Tuning PID control loops can be a time consuming task for process engineers. If a plant system contains dozens of PID controllers to control dozens of subsystems, tuning the overall system can require a large amount of engineering effort. The endeavor becomes truly formidable when a plant system with thousands of PID loops is considered. The present inventors have recognized a need for improved methods of tuning a distributed control plant system.